docs: def summed_probabilities(self, choosers, alternatives):
          """
          Returns the sum of probabilities for alternatives across all
          chooser segments.
  
          Parameters
          ----------
          choosers : pandas.DataFrame
              Table describing the agents making choices, e.g. households.
              Must have a column matching the .segmentation_col attribute.
          alternatives : pandas.DataFrame
              Table describing the things from which agents are choosing.
  
          Returns
          -------
          probs : pandas.Series
              Summed probabilities from each segment added together.
  
          """
          if len(alternatives) == 0 or len(choosers) == 0:
              return pd.Series()
  
          logger.debug(
              'start: calculate summed probabilities in LCM group {}'.format(
                  self.name))
          probs = []
  
          for name, df in self._iter_groups(choosers):
              probs.append(
                  self.models[name].summed_probabilities(df, alternatives))
  
          add = tz.curry(pd.Series.add, fill_value=0)
          probs = tz.reduce(add, probs)
  
          logger.debug(
              'finish: calculate summed probabilities in LCM group {}'.format(
                  self.name))
          return probs